Unlocking breeding potential of African crops through data management an

example with CASSAVABASE

Guillaume Bauchet

Plant and Animal Genome Conference San Diego January 2016

gjb99@cornell.edu

OUTLINE

http://nextgencassava.org/

CASSAVABASE , What  for?

CASSAVABASE , a  user  perspective

CASSAVABASE , search,  manage,  analyze

CASSAVABASE , a  view

The  Central  data  store  for  NEXTGEN CASSAVA :Genomic  selection  in  African  cassava  breeding  programs

http://nextgencassava.org/

NEXTGEN CASSAVA

What are the major challenges?

● Multi trait and Multi breeding environments for cassava phenotypic data collection

● Large scale production of genomic data using GBS

● Integrate Genomic Selection tool via web interface

What are the major challenges?

● Make the most of this resource for cassava breeders: speed up the analysis and decision making

What are the needs?● Search various data types (phenotypes and germplasm) in a large datastore

●Manage data and daily breeding activity through comprehensive interface

●Analyse and retrieve data for genomic assisted breeding

What are our solutions?● Integrate phenomic & genomic data with breeding tools

●Use Perl with the Bio::Chado::Schema and Natural Diversitymodule as database architecture

●Retrieve genomic information

●Sequence visualization ●Open source

https://github.com/solgenomics/

http://cassavabase.org/

New search bar

Navigation bar always visible on top Expandable search box

Caroussel

New responsive design

CASSAVABASEby numbers

2016: + 80,000 accessions, 2,5 billion genetic observations

2014:

+360 registered users

From Phenotype to Genotype to Breeding: Harvesting the fruits of CASSAVABASE

CASSAVABASE, an Office perspective: Search

Search breeding program, location, trial, trait, year, accession

CASSAVABASE, a field perspective: Manage Phenotypes

Define phenotypic traits via Cassava trait dictionaryin CASSAVABASE

Data collection

via FieldBookapp*

Design trials, barcodes & field maps

in CASSAVABASE*

Data uploading in CASSAVABASE

via .xls and .txt file **See Alex Ogbonna PAG presentation

“Managing Phenotypic Data through Cassavabase with Fieldbook App”“

Data analysis in CASSAVABASE

-Sum. stat-ANOVA-BLUP-GSIn CASSAVABASE

Design genotyping Trial in CASSAVABASE

TASSEL pipeline

Data filtering &

imputationGBS data uploading

In CASSAVABASE

GS Analysis & Visualization

in CASSAVABASE

GBS facility @ Cornell

CASSAVABASE, a lab perspective: Manage Genotypes

CASSAVABASE an office perspective: ManageBreeding programs, trial, accession

CASSAVABASE : Analyze with SolGS

Phenotypic values Population Structure GEBV vs phenotypes

See Isaak Tecle PAG presentation & poster 342“solGS: A Web-based Solution for Genomic Selection”

GEBV

CASSAVABASE : Analyze with SolGS

CASSAVABASE from the Office: Analyze phenotypesQC to phenotypes

Single trial

CASSAVABASE from the Office: Analyze phenotypesQC to phenotypes

Single trial

CASSAVABASE tools: Analyze pedigree

CASSAVABASE from the Office: Analyze phenotypes

data_2011_B1

4 6 8 10

r= 0.68

p<0.001

r= 0.66

p<0.001

4 6 8 10 14

r= 0.70

p<0.001

46

810

12

r= 0.63

p<0.001

46

810

data_2011_B2

r= 0.76

p<0.001

r= 0.79

p<0.001

r= 0.73

p<0.001

data_2011_B3

r= 0.76

p<0.001

46

810

r= 0.68

p<0.001

46

810

14 data_2012_B1

r= 0.75

p<0.001

4 6 8 10 12 4 6 8 10 4 6 8 12

46

812

data_2012_B2

30 31 32 33 34 35 36 37

-1.5

-0.5

0.5

1.5

Fitted values

Residuals

Residuals vs Fitted

26

9

15

-2 -1 0 1 2

-10

12

Theoretical Quantiles

Sta

ndar

dize

d re

sidu

als

Normal Q-Q

26

9

15

30 31 32 33 34 35 36 37

0.0

0.4

0.8

1.2

Fitted values

Standardized residuals

Scale-Location269

15

0.0 0.1 0.2 0.3 0.4 0.5

-2-1

01

2

Leverage

Sta

ndar

dize

d re

sidu

als

Cook's distance

Residuals vs Leverage

9

2615

ANOVA, h2,

BLUP, GxE

QC phenotypesMultiple trials

JBrowse

CASSAVABASE tools: Analyze sequence

Variant effects

prediction

VIGS tool

CASSAVABASE tools: Analyze sequence

BLAST

CASSAVABASE, a User perspective: support & interaction

CASSAVABASE, a User perspective: support & interaction

-> Provide support on technical issues ( data management)-> Gather user request for tool improvement and new developments (pedigree queries, VIGS)-> 2016: Install Mirror site @ IITA Ibadan, Nigeria

Weekly meetings with users in Africa: Wiki, FB pages & mailing list:

CASSAVABASE Upcoming developments

Search: Integrate trait & values in the wizard search

Manage: extract data subset according to their phenotypicvalues, conditionnal choices

Analyze: -Phenotypic analysis developments (ANOVA, GxE)-Pedigree analysis-Jbrowse: Mutation prediction of genetic variants-SolGS: Jobs queuing, trial selection improvement

LukasMueller

AlexOgbonna

BryanEllerbrock

NaamaMenda

IsaakTecle

NickMorales

AKNOWLEDGEMENTS

Jeremy Edwards

BMGF

ChiedozieEgesi

PeterKulakow

Robert Kawuki

IsmailRabbi

Questions?